Evidence map›Paper›PMID 40018153›Full record

ArticleBMJ public health2024

How much does government's short-term response matter for explaining cross-country variation in COVID-19 infection outcomes? A regression-based relative importance analysis of 84 countries.

Gordon G Liu, Xiaoyun Peng, Hanmo Yang, Junjian Yi

Abstract read
In one paragraph

Article in BMJ public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Gordon G LiuChina Center for Economic Research, National School of Development, Peking University, Beijing, Beijing, China.
Xiaoyun PengChina Center for Economic Research, National School of Development, Peking University, Beijing, Beijing, China.
Hanmo YangDepartment of Global Health and Population, T H Chan School of Public Health, Harvard University, Boston, Massachusetts, USA.ORCID 0000-0003-4848-0878
Junjian YiChina Center for Economic Research, National School of Development, Peking University, Beijing, Beijing, China.ORCID 0000-0002-4963-1052

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: We study the predetermined characteristics of countries in addition to their government non-pharmaceutical interventions (NPIs) to shed light on the correlates of the variation in COVID-19 infection outcomes across countries. Methods and analysis: We conduct a systematic investigation of the validity of government responses in 84 countries by gradually adding the predetermined cultural, natural and socioeconomic factors of each country using a fixed-effect model and daily panel data. A relative importance analysis is conducted to isolate the contribution of each variable to the R Results: Government NPIs are effective in containing the virus spread and explain approximately 9% of the variations in the pandemic outcomes. COVID-19 is more prevalent in countries that are more individual-oriented or with a higher gross domestic product (GDP) per capita, while a country's government expenditure on health as a proportion of GDP and median age are negatively associated with the infection outcome. The SARS-CoV-2 lifecycle and the impacts of other unobserved factors together explain more than half of the variation in the prevalence of COVID-19 across countries. The degree of individualism explains 9.30% of the variation, and the explanatory power of the other socioeconomic factors is less than 4% each. Conclusion: The COVID-19 infection outcomes are correlated with multivariate factors, ranging from state NPIs, culture-influenced human behaviours, geographical conditions and socioeconomic conditions. As expected, the stronger or faster are the government responses, the lower is the level of infections. In the meantime, many other factors underpin a major part of the variation in the control of COVID-19. As such, from a scientific perspective, it is important that country-specific conditions are taken into account when evaluating the impact of NPIs in order to conduct more cost-effective policy interventions.

Indexed as

Communicable Disease ControlEpidemiologyPublic Health

Identifiers

PMID40018153
PMCPMC11812740

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